Main
Timothy Keyes
I am a data scientist, bioinformatician, and cancer biologist. In my work, I develop statistical and machine learning algorithms for analyzing high-dimensional single-cell data and predicting clinical outcomes in cancer patients.
I am searching for a position at the intersection of biomedical data science, machine learning, and medicine where I can use data to solve problems relevant to human health.
Education
M.D./Ph.D. - Cancer Biology
Stanford University
Stanford, CA
Current - 2015
- National Cancer Institute (NCI) National Research Service Award fellow
- Advisors: Kara Davis and Garry Nolan
M.S. - Biomedical Informatics (concurrent with M.D./Ph.D.)
Stanford University
Stanford, CA
Current - 2020
B.A. - Psychology and Computational Neuroscience
Princeton University
Princeton, NJ
2014 - 2010
- Summa cum laude
- GPA: 3.99
Select Employment
Data Science Mentor - Posit Academy
Posit, PBC (formerly RStudio, PBC)
Stanford, CA
Current - 2022
- Leading group-based instruction and one-on-one mentoring for Posit Academy cohorts learning R and Python
- Engaging in regular professional development programming with experienced data science educators
Graduate Intern - Oncology Bioinformatics, gRED
Genentech, Inc
South San Francisco, CA
2022
- Codeveloped a novel algorithm for detecting transcription factor network perturbations in cancer using Bayesian network modeling
- Automated a multiomic data integration pipeline for ATAC- and RNA-seq
Select Publications
{tidytof}: A user-friendly framework for scalable and reproducible high-dimensional cytometry data analysis.
Under review (copy available upon request)
N/A
2022
- Keyes TJ, Koladiya A, Lo YC, Nolan GP, Davis KL.
- Project website: https://keyes-timothy.github.io/tidytof/
CytofIn enables Integrated Analysis of Public Mass Cytometry Datasets using Generalized Anchors
N/A
2022
- Lo YC, Keyes TJ, Jager A, Sarno J, Domizi P, Majeti R, Sakamoto KM, Lacayo N, Mulligan CG, Waters J, Sahaf B, Bendall SC, Davis KL
A cancer biologist's primer on machine learning applications in high-dimensional cytometry
N/A
2020
- Keyes TJ, Domizi P, Lo YC, Nolan GP, and Davis KL
Open-source software
tidytof: A user-friendly framework for interactive and highly reproducible cytometry data analysis
N/A
N/A
- An R package for analyzing high-dimensional cytometry data using the tidyverse
MARX: A novel algorithm for detecting cancer-specific single-cell features
N/A
N/A
- An R package that implements Matrix factorization and Residual Expression (MARX), an algorithm for comparing high-dimensional biological measurements to a lower-dimensional reference linear subspace
Leadership
Co-founder - Executive Board
Medical Student Pride Alliance, 501(c)(3)
Birmingham, AL
Current - 2018
- Co-founded national non-profit organization advocating for LGBTQ+ medical students
- Led Research & Analytics division, resulting in multiple publications
Awards
Stanford University School of Medicine
Stanford, CA
N/A
- American Society of Hematology (ASH) Abstract Achievement Award (2022)
- rstudio::global(2021) Diversity Scholarship (2021)
- Point Foundation Graduate Student Scholarship (2020)
- National Cancer Institute Ruth L. Kirschstein Pre-doctoral National Research Service Award (2019)
Teaching
Stanford University School of Medicine
Stanford, CA
2021 - 2017
- R for Data Science (2021)
- Immunology in Health and Disease (2017-2019)
Grants
Deep Neural Network Prediction of Relapse in Pediatric Acute Leukemia
The Mark Foundation for Cancer Research (ASPIRE II Award); $750,000
N/A
2024 - 2021
Computational Approaches to Predicting Post-treatment Relapse in Pediatric Acute Myeloid Leukemia
The Andrew McDonough B+ (Be Positive) Foundation; $150,000
N/A
2023 - 2018
References
Kara Davis, DO
Stanford University School of Medicine (PhD Co-advisor)
N/A
N/A
- email: kardavis@stanford.edu
Garry Nolan, PhD
Stanford University School of Medicine (PhD Co-advisor)
N/A
N/A
- email: gnolan@stanford.edu
